A Large-Scale Graph Learning Framework of Technological Gatekeepers by MapReduce

被引：2
|
作者：
Liu Tong [1 ]
Guo Wensheng [2 ]
机构：
[1] Beihang Univ, Sch Econ & Management, Beijing, Peoples R China
[2] China Univ Petr, Coll Geophys & Informat Engn, Beijing, Peoples R China
来源：
2012 IEEE 26TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM WORKSHOPS & PHD FORUM (IPDPSW) | 2012年
关键词：
Graph model; MapReduce; Technological gatekeepers;
D O I：
10.1109/IPDPSW.2012.248
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
MapReduce based graph learning algorithm is applied to the identification of technological gatekeepers in large-scale technological information flow network across large number of enterprises of several industries. Experiments show that the efficiency of MultiAdjacency Matrix algorithm is one time higher than PEGASUS. The effects of the number of cluster nodes and input file formats on the performance of the algorithm are also studied.
引用
收藏
页码：1997 / 2003
页数：7
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